Abstract The clinical success of T-cell receptor (TCR)-based immunotherapy depends on the efficacy and specificity of TCRs. Naturally occurring TCRs have limited anti-tumor potency due to their low affinity for tumor antigens. Affinity enhancement is a promising strategy to generate highly potent TCRs. However, it is concerned that affinity-enhanced TCRs are prone to lose specificity. We isolated low affinity TCRs specific for NY-ESO-1 157-165 /HLA-A*02:01 from peripheral blood mononuclear cells of healthy donors. An affinity-enhanced TCR candidate with optimal affinity and specificity was generated using phage display and an extensive set of in vitro and in vivo assays. Alanine scanning mutagenesis showed that the TCR candidate retained specificity by making extensive contacts to the side chains of NY-ESO-1 157-165 peptide. Adoptive transfer of T cells engineered with this candidate (termed TAEST16001) significantly inhibited tumor growth in subcutaneous, metastatic, and patient-derived xenograft (PDX) mouse tumor models. This study demonstrates that sophisticated engineering and screening techniques can be utilized to generate a clinical candidate TCR with potent anti-tumor activity without losing specificity. TAEST16001 was approved by the Center for Drug Evaluation (CDE) as the first TCR-based immunotherapy clinical trial in China ( ClinicalTrials.gov Identifier: NCT03159585 ).
The Web browser is a killer app on mobile devices such as smartphones. However, the user experience of mobile Web browsing is undesirable because of the slow resource loading. To improve the performance of Web resource loading, caching has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the performance of mobile Web caching. For example, most of these studies mainly focus on client-side implementations but not server-side configurations, suffer from biased user behaviors, and fail to study "miscached" resources. To address these issues, in this paper, we present a proactive approach for a comprehensive measurement study on mobile Web cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effective the caching works in practice. We report detailed analysis results of different websites and various types of Web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems -- Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content, Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile Web developers can do to mitigate those problems.
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